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Energy and the Environment
Criteria Air Pollutant and Greenhouse Gases Emissions from U.S. Refineries Allocated to Refinery Products Pingping Sun, Ben Young, Amgad Elgowainy, Zifeng Lu, Michael Q. Wang, Ben Morelli, and Troy Robert Hawkins Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b05870 • Publication Date (Web): 03 May 2019 Downloaded from http://pubs.acs.org on May 4, 2019
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Criteria Air Pollutant and Greenhouse Gases Emissions from U.S. Refineries Allocated to
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Refinery Products
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Pingping Sun,a Ben Young,b Amgad Elgowainy,a * Zifeng Lu,a Michael Wang,a Ben Morelli,b
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Troy Hawkinsa
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a
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Illinois 60439, USA.
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b
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02421, USA.
Energy Systems Division, Argonne National Laboratory, 9700 S. Cass Avenue, Lemont,
Eastern Research Group, Inc. (ERG), 110 Hartwell Avenue #1, Lexington, Massachusetts
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* Email:
[email protected] 1
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Abstract
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Using Greenhouse Gas Reporting Program data (GHGRP) and National Emissions Inventory
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(NEI) data from 2014, we investigate U.S. refinery greenhouse gas (GHG) emissions (CO2, CH4,
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and N2O) and criteria air pollutant (CAP) emissions (VOC, CO, NOx, SO2, PM10, and PM2.5). The
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study derives (1) combustion emission factors (EFs) of refinery fuels (e.g., refinery catalyst coke
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and refinery combined gas); (2) U.S. refinery GHG emissions and CAP emissions per crude
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throughput at the national and regional levels; and (3) GHG and CAP emissions attributable to
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U.S. refinery products. The latter two emissions were further itemized by source: combustion
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emission, process emission, and facility-wide emission. We estimated U.S. refinery product GHG
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and CAP emissions via energy allocation at the refinery process unit level. The unit energy demand
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and unit flow information were adopted from the Petroleum Refinery Life Cycle
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Inventory Model (PRELIM V1.1) by fitting individual U.S. refineries. This study fills an
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important information gap as it (1) evaluates refinery CAP emissions along with GHG emissions;
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and (2) provides CAP and GHG emissions not only for refinery main products (gasoline, diesel,
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jet, etc.), but for refinery secondary products (asphalt, lubricant, wax, light olefins, etc.).
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1 Introduction
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Petroleum refining is central to the U.S. economy. In 2016, petroleum energy supplied ~36% of
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the total energy used in the United States[1] ~92% of U.S. transportation energy demand,[1] despite
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recent increases in the use of alternative transportation fuels. Petroleum refining is also ubiquitous
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in the supply chains of myriad products, While one of the most important industrial sectors to
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power the activities of modern society, the petroleum refining sector is also one of the main sources
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of air emissions and other environmental releases. For example, in 2016, the U.S. refining sector
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accounted for 3.1% of total U.S. carbon dioxide emissions.[2]
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For global and U.S. national interests, as well as efforts to reduce adverse environmental impacts
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from anthropogenic activities,[3] it is important to identify and quantify related emissions. Given
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the importance of curbing refinery air emissions, researchers have been striving to identify
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petroleum refinery emission sources, quantify the emission amounts, and benchmark emissions 3
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allocated to transportation fuels. These studies have mostly focused on GHG emissions, especially
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on carbon dioxide (CO2) emissions. For example, Furoholt (1995)[4] studied eight general refining
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processes in Norwegian refineries and applied a process unit level allocation method to calculate
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energy use and emissions for individual refinery products. Furoholt[4] demonstrated that using a
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process unit level allocation led to results significantly different from those obtained from
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aggregate refinery level allocation. Wang et al. (2004)[5] developed a petroleum refinery process
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based approach of allocating energy use in a refinery to individual products, based on shares of
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final and intermediate petroleum products (by mass content, energy content, or market value), as
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they flow through refining process units. They used results from a notional refinery to estimate
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process-level operations and energy burdens. Skone and Gerdes (2009)[6] allocated refineries’
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energy use and emissions to gasoline, diesel, and jet fuels applying (1) aggregate data from EIA
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on process unit throughput, and (2) aggregate inputs of 1996 data from an API/National Petroleum
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Refiners Association survey to vacuum distillation, hydrotreating, catalytic reforming, alkylation,
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and isomerization units. Bredeson et al. (2010)[7] described a refinery model in which individual
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process unit throughputs could vary without constraints, in order to determine key operational
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parameters for CO2 emissions. Their work revealed that the most important factor driving a
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refinery’s energy requirement is the hydrogen content of the products in relation to the content of
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the crude.
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More recently, the study by Elgowainy et al.[8] and Forman et al.[9] investigated U.S. refinery
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emissions allocated to refinery products by using linear programing (LP) modeling to model the
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operations of 43 U.S. refineries, representing 70% of the total U.S. refinery capacity. The results
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were then aggregated to present U.S. national average GHG emissions associated with various
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refinery products. In parallel, Abella et al.[10] created the Excel-based Petroleum Refinery Life4
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cycle Inventory Model (PRELIM) to track refinery energy uses and GHG emissions. PRELIM
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provides a transparent representation of intermediate flows among refinery process units and GHG
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emissions from those process units to allow users to configure refineries and estimate the
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associated GHG profiles for each product. Both research efforts assigned GHG emissions to
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refinery products based on intermediate flows. The studies of Elgowainy et al.[8] and Forman et
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al.[9] provide improved industry characterization using actual refinery configurations but at the
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expense of transparency, due to the confidentiality of the underlying data, while PRELIM provides
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full transparency with some loss in facility-specific fidelity. Cooney et al.[11] used PRELIM
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together with other models to quantify the life cycle GHG profile of U.S. refinery products in 2014,
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building on earlier efforts by Skone et al. (2009),[6] from the same research group.
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This study adds to these previous efforts by updating GHG emissions and expanding evaluation
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metrics by including criteria air pollutant (CAP) emissions, since CAP emissions are regulated
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under the Clean Air Act by the U.S. Environmental Protection Agency (EPA) to protect public
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health and welfare.[12] CAP includes nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2),
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particulate matter (PM), carbon monoxide (CO), and lead (Pb). In addition to these pollutants,
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emissions reductions of volatile organic compounds (VOCs) are important in reducing ground-
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level ozone.[12]
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This study covers six CAPs—VOC, CO, NOx, SO2, PM less than 10 μm (PM10), and PM less than
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2.5 μm [PM2.5])—and three GHG pollutants (CO2, CH4, and N2O), by using refinery-specific
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emissions reported to EPA datasets of the Greenhouse Gas Reporting Program (GHGRP)[2] and
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the National Emissions Inventory (NEI).[13] This work uses 2014 emissions inventory data and
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combines that with 2014 U.S. refinery capacity and refinery operations information to estimate 5
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emissions (1) released from refinery fuel combustions, (2) per crude processed in U.S. refineries,
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and (3) associated with each refinery product.
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This study covers more than 98% of existing refineries and fills an information and data gap by
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benchmarking national and regional CAP emissions for the production of a full slate of refinery
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products.
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While previous studies quantify GHG emissions attributed to the production of major refinery
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products,[8,10,11] the present study updates refinery GHG emission with additional values.
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1. This study estimates refinery GHG emissions allocated to not only major refinery products,
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but also secondary refinery products, lubricant, light olefins, asphalt, and wax. These
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results provide valuable information for assessing the environmental impacts of other
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industries, such as the pavement and construction industry (asphalt), petrochemical
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industry (light olefins), manufacturing industry (lubricant), and others.
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2. The GHG results can validate the methodology used for CAP emission studies, such as
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allocating refinery-reported facility emissions to refinery process units and product pools.
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Because there is no previously reported CAP data, it is essential to use this kind of
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methodology to validate the reliability of the reported results.
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3. The variations in refinery operations and resultant variations in emissions (by year, region,
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facility, emission control technology, and many other factors) justify reporting complete
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air emission information based on consistent operation and emission data and methodology
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(consistent year, region, facility coverage, etc.).
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Quantifying refinery emissions is important for understanding the supply chain environmental
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impacts of transportation fuels and a wide range of petroleum-derived chemicals.[14] These refinery
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onsite GHG and CAP emissions allocated to refinery products constitute key elements in
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establishing baselines of full life cycle evaluations of various refinery products. However, it is
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worth noting that the present study solely focuses on refinery onsite GHG and CAP emissions
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(within the refinery fenceline), with the boundary consistent with the GHGRP and NEI data set.
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The additional information needed for full life cycle analyses is extensive and far beyond the scope
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of this study, and thus is not included here.
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2 Methodology
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This study compiles comprehensive inventories of U.S. refinery emissions (reported by facilities
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and including detailed data from process units), and information about U.S. refinery operations,
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such as unit capacity, utilization rate, material and energy input, and final products. A rigorous
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refinery list matching was conducted to ensure the same refinery facility coverage among emission
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datasets and refinery production datasets, based on cross-checks of physical location, history of
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acquisitions/mergers, and capacity.
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Obtaining the GHG and CAP emissions associated with refinery products requires an appropriate
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allocation approach to attribute refinery facility and/or unit emissions to refinery final products.
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This allocation is enabled by using the Petroleum Refinery Life Cycle Inventory Model
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(PRELIM V1.1)[15] and fitting each individual refinery facility to one of the PRELIM V1.1
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configuration models. The modeling results are subsequently aggregated at the Petroleum
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Administration for Defense Districts (PADD) level and at the national level. The aggregation at
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the PADD level is set by data availability, because some data sources (e.g. refinery fuel 7
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combustion, refinery utilization rate, refinery net products) are only available at PADD or sub-
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PADD level.
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2.1 Data Sources
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This study used several datasets to establish GHG and CAP emissions for U.S. refineries. These
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datasets support facility and process level assessments of emissions as reported directly by
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facilities. Using facility level data and adjusting regional or national assessments of production
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and fuel consumption reduces the uncertainty that might arise from non-reporting facilities.
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CAP Emissions
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CAP emissions data come from the National Emissions Inventory (NEI) database, which provides
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emissions data for CAPs, criteria precursors, and hazardous air pollutants from U.S. point,
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nonpoint, on-road, off-road, and event sources.[13] The NEI database is updated every three years,
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and 2014 was the most recent year for which NEI data was available when the present work was
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pursued.[13] NEI emission records are reported using eight-digit Source Classification Codes
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(SCCs) that correspond to process units within a facility. In total, 128 refineries representing 99.3%
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of operating capacity were identified in the NEI for the year 2014.
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GHG Emissions
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The Greenhouse Gas Reporting Program (GHGRP) requires businesses operating in certain sectors
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to report their annual emissions of CO2, CH4, N2O, and certain fluorinated GHGs from specific
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equipment and processes at their plants.
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source that provides process level GHG emissions at refineries. Different sectors are regulated and
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subject to report under different subparts of the GHGRP. Petroleum refineries are regulated under
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Subpart Y, hydrogen facilities are regulated under Subpart P, and combustion emissions from any
[2]
The GHGRP represents the sole U.S. national data
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facility are regulated under Subpart C. Collectively, GHGRP data was identified for 137 petroleum
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refineries reflecting 98.7% of operating capacity in 2014.
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Facilities can report emissions using continuous emission monitoring systems or through specific
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emission calculation methods approved by the EPA. This variation in reporting approaches might
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result in variable accuracy of emissions from various facilities, units, or combustion fuels.
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GHG emissions are reported at the process level, varying significantly depending on the subpart,
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calculation method, and process type. Unlike the NEI, the GHGRP datasets do not include SCCs
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and do not use consistent field names across all records. Therefore, we use a combination of
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process text and subpart-specific details to categorize emissions to process units.
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Itemized Emissions
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Emissions can be itemized by three groups: process emissions, combustion emissions, and facility-
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wide emissions (FWE). Process emissions are those emissions solely sourced from and specific to
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certain refinery units (e.g., atmospheric distillation tower, alkylation unit), which are assigned to
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the appropriate units based on SCC or unit description. Combustion emissions are emissions from
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heat and steam generation; they result from the combustion of fuel to supply energy. FWEs are not
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specific to certain refinery conversion/separation process units; instead, they cover the emissions
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throughout the overall facility, such as the emissions from cooling water supply system, waste
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water treatment plant (WWTP), and flare, fugitive, tanker and other auxiliary processes. We
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allocated combustion and FWEs to refinery process units using the approach discussed in Section
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2.4.
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U.S. Refinery Fuel Consumption
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The U.S. Energy Information Administration (EIA) provides the fuel consumption of petroleum
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refineries, organized by PADD,[16] including refinery still gas, refinery catalyst coke, natural gas,
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and other fuels. The “other fuels” category includes “pentanes plus other hydrocarbons,
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oxygenates, hydrogen, unfinished oils, gasoline, special naphtha, jet fuel, lubricants, asphalt and
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road oil, and miscellaneous products.”[16] The portion of natural gas used as feedstock for hydrogen
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production[17] is excluded from the total natural gas (fuel) consumption at refineries. Table S1 in
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Supporting Information (SI) shows the facility coverage of each refinery fuel in the NEI and
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GHGRP dataset.
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The fuel volumes are converted to energy units using the lower heating value (LHV) of fuel
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provided by the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation
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(GREET®) model from 2016,[18] which is shown in Table S2 in the SI.
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To estimate fuel consumption consistent with the facilities for which emissions data are available,
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we scale fuel consumption by PADD based on the throughput of refineries that report emissions.
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(Table S3 shows adjusted fuel comsumptions to match the NEI dataset.) SI Tables S4 and S5 show
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the compiled GHG and CAP emissions from refinery fuel combustion in each PADD. In all cases,
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emissions data are available for facilities accounting for more than 95% of the PADD total crude
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inputs.
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Refinery Capacity and Throughput
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U.S. refinery capacity information is published annually in the EIA’s Refinery Capacity dataset,[19]
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and refinery capacity utilization is published for each sub-PADD district.[20] The refinery capacity
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utilization is used to calculate the actual crude processed at sub-PADD level. In 2014, 145 unique 10
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refineries were present across datasets. Of those, 124 were present across relevant datasets (EIA,
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NEI, and GHGRP), representing 98% of total operating capacity. Figure S3 in the SI shows a
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general unit process layout for a complex U.S. petroleum refinery.
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Refinery unit throughputs are calculated based on the capacity of each unit provided by the EIA
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Refinery Capacity dataset.[21] PADD sub-districts utilization rates are used to adjust unit
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throughput, because utilization rates by refinery and process unit are not available. Total operating
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capacity at each facility is calculated by subtracting idle capacity from operable capacity.[21] The
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unit throughput (Tu) for each unit at each refinery is calculated as shown below:
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𝑻𝒖 = 𝑼𝒏𝒊𝒕 𝑪𝒉𝒂𝒓𝒈𝒆 𝑪𝒂𝒑𝒂𝒄𝒊𝒕𝒚
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(1)
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Unit charge capacity: Capacity of input feed to the refinery unit
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Operating capacity: refinery capacity in active operation, in barrels of crude oil input,
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Operable capacity: refinery capacity that is capable of active operation, including both operating
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capacity and idled capacity, in barrels of crude oil input.
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The unit throughputs, Tu, of each refinery can be aggregated to the national and PADD levels (see
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Table S13 in the SI).
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Refinery Product Outputs
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The EIA reports final refinery products in its net production at refineries dataset.[22] The EIA-
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reported refinery products are used as a reference to aid in allocating refinery emissions to
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products.
(
)
𝒃𝒃𝒍 𝑶𝒑𝒆𝒓𝒂𝒕𝒊𝒏𝒈 𝑪𝒂𝒑𝒂𝒄𝒊𝒕𝒚 (𝒃𝒃𝒍 𝒑𝒆𝒓 𝒄𝒂𝒍𝒆𝒏𝒅𝒂𝒓 𝒅𝒂𝒚) × 𝑪𝒂𝒍𝒆𝒏𝒅𝒂𝒓 𝒅𝒂𝒚 𝑻𝒐𝒕𝒂𝒍 𝑶𝒑𝒆𝒓𝒂𝒃𝒍𝒆 𝑪𝒂𝒑𝒂𝒄𝒊𝒕𝒚 (𝒃𝒃𝒍 𝒑𝒆𝒓 𝒄𝒂𝒍𝒆𝒏𝒅𝒂𝒓 𝒅𝒂𝒚) × 𝑼𝒕𝒊𝒍𝒊𝒛𝒂𝒕𝒊𝒐𝒏 𝒓𝒂𝒕𝒆 (%) × 𝟑𝟔𝟓
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2.2 Emission Factors Calculations
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In U.S. refineries, the combustion processes for energy supply drive a significant portion of
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refinery emissions. Emissions related to refinery fuel combustion are normalized to fuel use
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(dividing the amount of emission by the amount of fuel combusted) to develop fuel-specific
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combustion emission factors.
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The NEI database categorizes combustion emissions by fuel type (through combustion-related
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SCCs), including coal, distillate, liquefied petroleum gas (LPG), residual fuel oil, natural gas,
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refinery still gas, and other combustion fuels. Other combustion fuels include gasoline, jet fuel,
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and combustion of waste products.[13] Emissions produced by combustion for heat supply at
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specific refinery units such as fluid catalytic crackers (FCCs) are also categorized by fuel type.
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Flares are not included as fuel consumption because they are not a steady source of energy supply.
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Combustion emissions for each fuel are summed to the national or PADD level. Only facilities
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that match across NEI and EIA datasets are included in the emission aggregation.
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2.3 Refinery Emissions per Crude Throughput
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The refinery emission intensity per unit of crude throughput at the facility level can be derived by
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dividing the refinery facility emission amounts[2,13] by the refinery crude throughputs.[20,21] The
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emissions per crude input are also itemized to process emissions, combustion emissions, and FWEs.
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2.4 Refinery Emissions Allocated to Refinery Products
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Previous research efforts[23] have developed an approach to allocate the refinery facility and
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process emissions to individual refinery products at the refinery unit level by modeling refinery 12
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operations with LP modeling. Refineries use LP modeling to optimize refinery operations, which
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maximizes refinery profits. LP modeling is refinery-specific, and needs to be constructed based on
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very detailed refinery configurations. This information is often confidential, so constructing the
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LP models is often costly and time consuming. The present work executes unit-level allocations
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using PRELIM.[15] With built-in typical refinery configurations, PRELIM provides some typical
244
energy flow and mass flow information that are sufficient to guide the process-unit-level allocation.
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PRELIM V1.1
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PRELIM is a life-cycle inventory spreadsheet that can model energy use and GHG emissions based
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on customizable crude assays and unit configurations. PRELIM has 10 built-in typical refinery
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configurations representing different refinery conversion capabilities: four simple configurations,
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three coking refinery configurations, and three hydrocracking refinery configurations[15] (units
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included are summarized in Table 2 in the PRELIM user manual).[24] In the present study,
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individual U.S. refinery operations in 2014 were modeled by fitting one of the PRELIM V1.1
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refinery configurations[15] with EIA-reported crude throughput. The strategy of matching
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individual U.S. refineries with PRELIM V1.1 configurations was adopted from previous research
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by Cooney et al. (2016).[11]
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PRELIM V1.1 requires crude slate specifications. Because individual refinery crude slates
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information is absent, the present study simplifies the crude slate by using one crude slate as
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surrogate for all individual refineries. The selected crude surrogate was West Texas Sour, with
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API 31.7–34.1° and a sulfur content of 1.28–1.31 wt%,[15,25] because it is used in U.S. refineries
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and is similar to the average crude API of 31.8 and sulfur content of 1.45 used in U.S. refineries
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in 2014.[26] The simplification of using one crude slate in the present study is expected to have 13
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limited impact on allocating refinery emissions to refinery products. This is because the present
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study does not model refinery emissions (i.e., create emissions data); instead, it allocates the
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known refinery emissions to refinery products by adopting the model energy flow information,
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which is dependent on configuration and independent of crude slates.[24]
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Refinery Unit Energy Intensity and Unit Energy Use
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Unit energy intensity values (fuel use, electricity use, and steam use) were developed based on
267
values reported in PRELIM V1.1 and documented by Pellegrino et al.[27] and Szklo et al.[28] A
268
boiler efficiency of 80% is assumed by adopting the value from the GREET 2016 model.
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Pellegrino et al.[27] provide values for additional units not included within PRELIM V1.1 (e.g.,
270
lubricant production) and provides confirmation of reported energy demand. Table S14 in the SI
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shows the energy intensities of various refinery units.
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Most units obtain energy from the general heater and boiler system, and thus share emission
273
burdens from refinery fuel combustion. However, there are some exceptions:
274
FCC units often do not need heat or steam from the general heat and steam supply system.
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They are self-sufficient during process operation because they combust FCC catalyst coke
276
during catalyst regeneration.[29]
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Fluid coker and flexi coker (there are only a handful of these units in U.S. refineries [21] as
278
most coker units are delayed cokers) combust coke formed in process to supply energy. Thus,
279
like FCC units, the fluid coker and flexi coker units do not demand energy from the general
280
heat and steam supply system.
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Estimates of process unit energy intensity are combined with unit throughputs to estimate the total
282
heat and steam demand in each refinery. The percentage share of energy uses for each refinery 14
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process unit can be calculated within each refinery and aggregated to national results, as shown in
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Table S15 in the SI. The resultant energy uses in individual facilities can be aggregated to the
285
PADD and national levels, as shown in Table S16 in the SI. The refinery energy uses derived from
286
unit energy intensity can be validated by comparing them with EIA reported energy uses (also
287
shown in Table S17 in the SI). The difference of only 2% energy use validates the present approach
288
to estimating unit energy use.
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Allocating Refinery Facility Emissions to Units
290
The GHG and CAP emissions of individual refinery units can be categorized into three sources:
291
process unit emissions, combustion emissions, and FWEs.
292
Process emissions that NEI specifies for each unit are assigned to individual refinery process units
293
based on details provided in the NEI and GHGRP dataset.
294
The combustion emissions from heaters and boilers are allocated to refinery process units based
295
on the units’ respective shares of each energy source (shown in Table S15 in the SI). This is
296
because the GHGRP and NEI datasets do not specify combustion emissions related to each unit
297
from the facility-wide heat/steam system. This allocation is performed at each individual refinery
298
to better reflect each refinery’s unit throughput and configuration.
299
Some refinery FWEs — cooling tower, WWTP, and engines (mostly internal combustion engines),
300
categorized as FWE-1 — are also allocated to units based on the unit energy demand share
301
(combined heat and steam demand). This is because these emissions are proportional to water use
302
or engine use, which are in turn proportional to the process unit energy demand.[30] Other FWEs
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(fugitive, flare emissions, incinerator, tank, and others, categorized as FWE-2), do not correlate to
304
unit energy use, and are allocated to refinery products directly based on the product energy content. 15
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The refinery unit GHG and CAP emissions (aggregated to the national level), after allocations of
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combustion emissions and FWE-1, are shown in Table S18 in the SI. The refinery GHG and CAP
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emissions are mainly sourced from the atmospheric distillation tower, catalytic reformer, FCC
308
unit, hydrogen plant, and hydrotreating units (for diesel, gasoline, naphtha, and gasoil). Note that
309
these units have different capacities, because they process different cuts (portions) of crude slates
310
and have differing prevalence in U.S. refineries. Considering the capacity factor, it is useful to
311
compare the unit emissions per unit throughput, or unit emission intensity, as shown in Table S19
312
in the SI. Accounting for the capacity difference of various refinery units shows that the most
313
emission-intensive units are the lubricant production, thermal cracking, alkylation, catalytic
314
reformer, and FCC units. This is expected, because these units are energy-intensive and thus bear
315
greater emission burdens from fuel combustion, consistent with previous research results.[8]
316
Refinery Product Outputs Modeling and Matching with EIA Reported Products
317
Products reported by EIA are matched to product categories in PRELIM V1.1 in order to relate
318
PRELIM-derived allocation factors to actual U.S. refinery products (see Table S21 in the SI). This
319
categorization matching is essential for an accurate allocation of refinery emissions to products,
320
because PRELIM V1.1 and the EIA report use somewhat different nomenclature.[22] Some
321
important variations are discussed in Section 5 in the SI. The model-derived refinery final products
322
show divergence (to various extents) from EIA reported products, due to deviations in refinery
323
configuration, operation, and various assumptions embedded in the model. The differences are
324
discussed in Section 6 in the SI.
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325
Allocating Refinery Process Unit Emissions to Final Products
326
Upon establishing the correspondence between PRELIM-derived products and EIA final products
327
(Table S21 in the SI), the factors for allocating refinery process unit emissions to refinery unit
328
products can be developed in PRELIM V1.1. These factors are calculated for each refinery facility
329
and aggregated at the PADD or national level based on a production weighted average. The
330
PRELIM V1.1–derived PADD and national unit allocation factors need some adjustments to better
331
reflect U.S. refinery productions. For example, a single PRELIM V1.1 final product (e.g.,
332
Jet-A/AVTUR) matches multiple EIA products (aviation gasoline, kerosene, naphtha), so further
333
allocation (splitting) is required to complete the allocation to EIA final products. Another example
334
concerns the burdens allocated to refinery still gas, which need to be reallocated to all other
335
products because refinery still gas is typically combusted onsite for energy supply. In particular,
336
the present study develops an original and important allocation method to allocate refinery
337
emissions to lubricant production (see Figure S6 in the SI), because PRELIM does not include
338
lubricant units. More details regarding EIA product splitting, refinery still gas emission burdens,
339
and lubricant production emissions appear in Section 7 in the SI.
340
Figure 1 summarizes the overall approach of allocating refinery facility emissions to refinery
341
products, mostly via unit-level allocation.
17
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342 343 344
Figure 1. Summary of How Refinery Emissions Are Allocated to Refinery Products (BOB refers to blendstock for oxygenate blending)
345
3. Results and Discussion
346
3.1 U.S. Refinery Fuel Combustion GHG and CAP Emission Factors
347
Figure 2 shows the shares of refineries GHG and CAP emissions in 2014 from the combustion of
348
various refinery fuels (the magnitudes of these emissions are provided in Tables S4 and S5 for
349
GHG and CAP emissions, respectively). At the national level, most combustion-related emissions
350
from refineries are from the use of refinery still gas and natural gas, followed by refinery catalyst
351
coke. Together, these account for between 91% and 100% of emissions across all pollutant species
352
tracked. The use of other fuels such as coal, distillate, and residual fuel oils varies across PADDs
353
but represents only a minor contribution to total emissions.
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354 355
Figure 2. Share of Combustion Emissions by Fuel Type for U.S. Refineries in 2014
356
As the dominant energy source, combined gas leads all criteria air pollutant emissions, especially
357
for VOC, CO, and NOx.
358
In the present study, the emissions from natural gas and refinery still gas are combined because it
359
is speculated that the consumption and emissions of two gases are not well differentiated in
360
refineries, which likely causes reporting inconsistencies in fuel consumption and combustion
361
emissions. Refinery still gas and natural gas are often used in the same combustion units at
362
refineries and the gas supply is adjusted depending on refinery and market conditions. Many
363
individual facilities do not report refinery still gas consumption or report no natural gas
364
consumption, both of which are unlikely. Furthermore, carbon dioxide releases from fuel
365
combustion should be consistent across all combustion technologies, based on the carbon content
366
of the fuel. However, carbon dioxide emissions estimates from reported natural gas combustion
367
are significantly lower than the normal range, while emissions from reported refinery gas
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368
consumption are significantly higher than the normal range, indicating some reporting errors
369
through mis-categorizating fuel types.
370
Emission factors by fuel type are calculated by dividing total emissions by total fuel consumption.
371
Emission factors are calculated for the fuels that are included in both the emission dataset and the
372
fuel consumption dataset, aggregated at the national and PADD levels. Table 1 shows GHG and
373
CAP emission factors for refinery catalyst coke in each PADD, and Table 2 shows the same for
374
refinery combined gas in each PADD. Tables S6 through S9 in the SI show the emission factor for
375
other fuels, distillate, “other” fuel, residual oil, and LPG. The emission factors for coal combustion
376
were only available for PADD 1. Therefore, the results are not shown as PADD comparisons, but
377
are listed later in the national average result.
378 379
Table 1. Emission Factors for Combustion of Refinery Catalyst Coke in U.S. Refineries in 2014 by PADDs , g/MJ for CO2 and mg/MJ for Other Pollutants Catalyst Coke Emission Factor (g/MJ for CO2 and mg/MJ for Other Pollutants) Pollutant
PADD 1
PADD 2
PADD 3
PADD 4
PADD 5
United States
CO2
98.2
99.7
91.3
98.9
104.5
95.9
CH4
3.7
3.1
2.8
3.5
3.0
3.0
N2O
0.7
0.6
0.6
0.6
0.6
0.6
VOC
0.4
2.7
2.2
4.8
2.5
2.3
CO
3.0
16.4
12.9
8.9
15.4
12.9
NOx
20.3
17.9
10.2
13.9
7.6
12.5
SO2
23.6
15.8
11.3
30.0
7.6
13.5
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Catalyst Coke Emission Factor (g/MJ for CO2 and mg/MJ for Other Pollutants)
380 381
Pollutant
PADD 1
PADD 2
PADD 3
PADD 4
PADD 5
United States
PM10
11.3
18.9
10.0
36.5
4.1
12.0
PM2.5
10.43
17.1
9.1
29.6
3.3
10.7
Table 2. Emission Factors for Combustion of Combined Natural Gas and Refinery Still Gas in U.S. Refineries in 2014 by PADD, g/MJ for CO2 and mg/MJ for Other Pollutants. Combined Gas Emission Factor (g/MJ for CO2 and mg/MJ for Other Pollutants) Pollutant
PADD 1
PADD 2
PADD 3
PADD 4
PADD 5
United States
CO2
56.8
56.6
58.5
63.9
56.2
57.7
CH4
2.9
3.1
3.5
3.8
2.5
3.2
N2O
0.6
0.6
0.7
0.7
0.5
0.6
VOC
1.2
2.3
2.2
2.9
3.2
2.4
CO
20.1
25.9
12.9
39.4
15.2
17.2
NOx
33.1
37.7
29.6
41.8
29.4
31.8
SO2
3.4
6.6
5.6
11.8
8.1
6.4
PM10
6.2
5.8
4.0
4.7
3.9
4.5
PM2.5
5.3
5.4
4.0
4.3
3.8
4.3
382 383
Refinery fuel emission factors vary significantly by fuel source and by PADD. Not only are they
384
determined by fuel properties (carbon density, sulfur content, heating values, etc.), they are highly 21
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385
affected by combustion technology/practice, emission control technology/practice, refinery
386
operations, and other factors. Relative to refinery combined gas, refinery catalyst coke typically
387
has lower emission factors for VOCs, CO, and NOx, but higher emission factors for SO2, PM10,
388
and PM2.5. These results reflect the PADD average emission conditions in 2014.
389
Refinery combined gas and catalyst coke are the main fuels used in refineries, producing 98% of
390
total refinery energy generated onsite. Their distinctive features (gas and solid state) differentiate
391
them from other fuels (liquid state) make them less prone to reporting errors by miscategorizing
392
fuel types. In addition, a high percentage of the emissions from coke combustion and refinery gas
393
combustion was reported based on measured data or process-specific considerations as opposed to
394
data calcuated with general formulas. All these factors contribute to robust and reliable emission
395
factor results for catalyst coke and refinery gas.
396
The CO2 emission factors of distillate, residual oil, other fuel, and LPG show some inconsistency
397
among PADDs, indicating the mismatch of GHG emissions data and fuel consumption data, likely
398
caused by reporting errors. However, it is worth mentioning that GHG emissions come from the
399
GHGRP database and CAP emissions come from the NEI database, and the two databases are
400
independent of each other. Therefore, the lower reliability of GHG emission factors of distillate,
401
residual oil, other fuel, and LPG does not indicate that CAP emissions are less reliable for these
402
fuels.
403
Comparison of Emission Factors with Other Data Sources
404
Emission factors for CAPs for each fuel type are compared to previously published emission
405
factors developed for AP-42 and GREET 2016
406
provides some default emission factors,[2] which are listed in Table 3 for comparison.
[18,31]
if they are available. The GHGRP also
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Table 3. Comparison of This Study’s Emission Factors, National Results Aggregated with Those from AP-42, GHGRP, and GREET (2016),g/MJ for CO2 and mg/MJ for All Others Pollutant
Present
AP42a
GHGRP
GREET
Present
AP42b
Catalyst Coke
GHGRP
GREETc
Combined Gasd
CO2
95
--
95
104
58
52
50
56
CH4
2.9
--
2.8
1.1
3.2
1.0
0.9
1.0
N2O
0.6
--
0.6
0.9
0.6
0.3
0.1
0.3
VOCs
2.3
--
--
0.5
2.4
2.4
--
2.4
CO
13.3
--
--
22.7
17.1
37.0
--
20.8–23.7
NOx
12.3
--
--
113.7
32.2
14.2–83.4
--
34.1–38.9
SO2
13.3
--
--
511.8
6.4
0.3
--
0.3
PM10
12.3
--
--
2.6
4.5
3.3
--
3.3
PM2.5
10.4
--
--
2.4
4.4
--
--
3.3
Present
AP42e
GHGRP
GREET
Present
AP42f
GHGRP
GREETg
Pollutant LPG
Distillate
CO2
4.4
63.5–72.0
58.7
64.4
123.2
70.1
70.1
73.0–73.9
CH4
0.2
1.0
2.8
1.0
4.8
--
2.8
0.19–4.0
N2O
0.0
4.5
0.6
4.5
0.9
--
0.6
0.6–0.9
VOCs
0.5
--
--
4.1
113.7
--
--
--
CO
0.9
--
--
3.3
246.4
407.6
--
19.9–625.6
NOx
3.5
--
--
65.4
691.9
--
--
51.2–1990.4
SO2
0.1
--
--
89.1
123.2
--
0.5
PM10
0.2
--
--
3.5
69.2
132.7
--
7.7–52.1
PM2.5
0.2
--
--
3.5
57.8
--
--
5.2–51.2
Present
AP42h
GHGRP
GREET
Present
AP42i
GHGRP
GREET
Pollutant Residual Oil CO2
68.2
--
70.1
Coal 80.5
142.1
91.0–123.2
88.1
94.7
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Pollutant
Present
AP42a
GHGRP
GREET
Present
AP42b
GHGRP
GREETc
CH4
2.7
--
2.8
3.0
17.1
0.19–15.2
10.4
1.1
N2O
0.5
--
0.6
1.6
2.5
0.6–1.5
1.5
0.8
VOCs
15.2
--
--
--
11.4
--
--
0.4
CO
78.7
15.2
--
34.1
142.2
9.5–208.5
--
22.7
NOx
436.0
30.3–170.6
--
132.7
350.7
132.7–587.6
--
113.7
SO2
398.1
436.0–483.3
--
644.5
1516.5
587.6–720.3
--
511.8
PM10
142.2
6.2–30.3
--
33.2
28.4
1.3–246.4
--
2.6
PM2.5
113.7
--
--
15.2
27.5
0.61–104.3
--
2.4
409
a. Catalyst coke EF is reported in AP-42 with different unit, g/m3 fresh feed.
410
b. Range of natural gas fired boilers.
411
c. Range of natural gas utility boilers.
412
d. The refinery fuel mix combustion emission factors are compared to the natural gas combustion emission factors.
413
e. Range of industrial and commercial boilers.
414
f.
415
g. Range of distillate fired boilers and diesel powered reciprocating engines.
416
h. Range of boilers for residual oil.
417
i.
Uncontrolled diesel engines.
Range of coal combustion boiler configurations; various control technologies may further reduce NOx, SO2, or PM.
418
AP-42[31] and the GREET model[18] cover a wide range of emission factors, reflecting the
419
variability of combustion technology, emission control technology, or fuel characteristics. Catalyst
420
coke is an important refinery fuel, but its emission factors are rarely reported, likely because the
421
catalyst coke is not recoverable in a concentrated form.[16] AP-42 reported catalyst coke emission
422
factor per cubic meter of feed. For comparison, the catalyst coke EF from the present study was
423
converted to the same unit and is shown in Table S10 in the SI. The comparison shows that the
424
present study’s EFs are one to three orders of magnitude lower than those of AP-42. The difference
425
might be caused by the changes in refinery operations and practices in the past decades, as the 24
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426
catalyst coke EF in AP-42 reflects refinery practices in 1960s–1970s,[31] while the results from the
427
present study reflect U.S. refinery practice in 2014. A study by Nelson and Nguyen[32] shows that
428
U.S. refinery CAP emissions decreased by 46–91% from 1990 to 2013 with the application of
429
emission control technologies. Another factor that could contribute to catalyst coke SO2 reduction
430
is the increased application of gas oil hydrotreating, which reduces the sulfur content of FCC unit
431
feedstock. From 1995 to 2014, U.S. national gas oil hydrotreating capacity increased by 45% to
432
2.9 million bbl/stream day.[33] GREET 2016[18] adopted the properties of petroleum coke to
433
estimate catalyst coke emission factors. It will likely overestimate the emission factors of catalyst
434
coke, because petroleum coke and catalyst coke are produced from different refinery reaction
435
processes (coker unit versus FCC unit) and using different feedstocks (vacuum residual oil versus
436
gasoil). The heavier and sourer vacuum residual oil (relative to gasoil) likely results in higher
437
carbon content and higher sulfur content in petroleum coke than in catalyst coke, leading to higher
438
combustion emission factors for petroleum coke.
439
The present study shows a higher combined gas CO2 emission factor than AP-42 and previous
440
GREET (2016) results because there is a higher carbon content in the ethane, and a higher share
441
of ethane in the refinery still gas than in the natural gas, which is primarily methane.
442
In the present study, LPG emission factors are very different from those of AP-42 and GREET.
443
Refineries do not commonly use LPG as a fuel (see Table S1). Therefore, emission factors derived
444
from its use in refinery operation are less representative, and might be more susceptible to reporting
445
errors. In particular, the very low CO2 emission factor from LPG indicates a low reliability.
446
The present study also shows a higher distillate CO2 emission factor than AP-42 or GREET 2016.
447
Comparing the difference in numbers of facilities reporting the use of distillate and the use of other 25
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448
fuels the NEI and GHGRP pools indicates that fuel type may have been mis-categorized for
449
distillate and other fuel (e.g., gasoline, jet) in GHGRP reporting. Meanwhile, the NEI dataset
450
includes 89 facilities that report distillate emissions. This makes the CAP emission factors more
451
reliable than GHG emission factors. The CAP emission factors estimated here are in line with
452
those reported by AP-42 and the GREET module.
453
The residual oil GHG and CAP emission factors from the present study are also in line with those
454
of AP-42 and GREET. This might be because residual oil is more distinguishable from other liquid
455
fuels used in refineries (distillate and other fuel), and thus less likely to be mis-categorized.
456
Overall, the major fuels used in refineries are catalyst coke and refinery combined gas. Together,
457
these account for more than 98% of the combustion energy generated onsite. The significant
458
facility coverage for catalyst coke and refinery combined gas (natural gas and still gas) make the
459
dataset less vulnerable to individual refinery reporting errors, which provides confidence in data
460
quality. The moderate facility coverage of residual oil use and distillate use in the NEI pool makes
461
the CAP emissions factors of these two fuels reasonably reliable. There are data inconsistencies
462
for the GHG combustion emission factors for LPG, distillate, and coal, indicating lower reliability.
463
3.2 U.S. Refinery CAP Emissions per Crude Throughput
464
The regional emissions by PADD per refinery throughput were investigated by dividing refinery
465
PADD-level emissions by PADD refinery crude throughput (that is equal to refinery operating
466
capacity multiply refinery utilization rates). Note that these values are not combustion factors of
467
crude oil; they are the overall refinery facility emissions averaged to crude throughput. Figure 3
468
shows the CAP and GHG emissions, and the data are also shown in Table S11 in the SI. 26
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469 470 471 472
Figure 3. Refinery CAP and GHG Emissions per Refinery Crude Throughput by PADD (The left y‒axis refers to mg CAP/MJ Crude and the right y‒axis refers to g CO2,eq/MJ crude).
473
Figure 3 shows that among the various PADDs, PADD 4 has the highest CAP emissions per unit
474
crude input. This is consistent with the fuel combustion results, which show that PADD 4 refineries
475
have higher CAP emission factors (for combined gas and catalyst coke) than the other PADD
476
refineries. In contrast to the trend of CAP emissions, the highest GHG emission per crude
477
throughput was observed for PADD 5. This is likely caused by the more complex refinery
478
configurations in PADD 5,[8] in response to processing heavy crude. The more complex refinery
479
configuration includes more process units that are often energy-intensive, which increases GHG
480
emissions. Note that CAP emissions do not necessarily track GHG emissions. Although CAP
481
emissions are largely related to combustion, environmental emissions are also influenced by
482
emission control technology, whereas CO2 emissions are determined by fuel properties in the
483
absence of carbon sequestration. 27
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484
Each PADD has different refining capacities, as shown in Table S12 in the SI. The contribution
485
of each PADD to national emissions, weighted by its capacity share, is shown in Figure S1 in the
486
SI. For all CAP and GHG pollutants, PADD 3 has the largest contribution of pollutant emissions,
487
because it has the largest capacity share (over 50% of national refinery capacity). Although PADD
488
4 has the highest emissions per unit of crude input, it only contributes a small portion of national
489
emissions, due to its small share in national refinery capacity (3.5%).
490
Note that emissions per crude throughput are not dependent on assumptions about crude slate or
491
refinery operations, because they are calculated based on GHG and CAP emissions reported to the
492
GHGRP and NEI, respectively, divided by crude throughput reported by EIA.
493
The present study shows that U.S. refineries have national average GHG emissions of 5.6 g
494
CO2,eq/MJ crude (5.0–7.1 g/MJ for various PADD refineries), consistent with the Abella and
495
Bergerson 2012[10] study. Abella and Bergerson[10] modeled GHG emissions by using PRELIM
496
V1.1 to simulate refinery processes with various configurations and operation scenarios. Among
497
the studied crude oils, the modeled GHG emissions were about 5.5–9.5 g/MJ crude for the
498
conventional crude oils with an API of 29.6–34.9° and sulfur content of 1.4–2.3 wt%. Note that in
499
2014, U.S. refineries used crudes with an average API of 31.8° and a sulfur content of 1.45 wt%;
500
the average properties are close to the properties of conventional crude oils.[26]
501
One study conducted for the American Fuel & Petrochemical Manufacturers organization by
502
Nelson and Nguyen[32] shows that NOx pollutant per crude input in refineries decreased to 100 g
503
NOx/m3 crude in 2011. The present study shows NOx emission of 2.32 g/MJ (84 g/m3) crude in
504
2014, comparable with the results from the Nelson and Nguyen study.
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505
Table 4 lists national emissions per crude processed in terms of process emissions, combustion
506
emissions, and FWEs (described in the Methodology section). The three emission shares from
507
each emission category are also shown in Figure S2 in the SI.
508
Table 4. U.S. Refinery GHG and CAP Emissions per Crude Throughput in 2014 Process Emissions 0.62
Combustion Emissions 4.84
Facility-wide Emissions 0.08
Total Emissions 5.54
CH4 (mg/MJ crude)
0.05
0.24
0.57
0.86
N2O (mg/MJ crude)
0.00
0.05
0.00
0.05
GHG (g CO2eq/MJ crude)
0.62
4.86
0.10
5.58
VOC (mg/MJ crude)
0.05
0.17
1.56
1.78
CO (mg/MJ crude)
0.05
1.09
0.39
1.53
NOx (mg/MJ crude)
0.04
2.00
0.29
2.32
SO2 (mg/MJ crude)
0.06
0.62
0.26
0.94
PM10 (mg/MJ crude)
0.02
0.43
0.18
0.63
PM2.5 (mg/MJ crude)
0.01
0.40
0.13
0.55
U.S. Weighted Average CO2 (g/MJ crude)
509 510
For most pollutants, such as CO2, N2O, CO, NOx, PM10, and PM2.5, the major source of emissions
511
is combustion. In contrast, CH4 and VOC emissions mainly come from FWEs. CH4 is mainly from
512
flare and fugitive emissions, while VOC is mainly sourced from fugitive and tank emissions.
29
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513
3.3 U.S. Refinery GHG and CAP Emissions per Refinery Product
514
With the refinery emission information and refinery products information, the GHG and CAP
515
emissions can be allocated to refinery products via the allocation approach described in Section 2,
516
by using PRELIM to implement unit-level allocation.
517
U.S. National Refinery Unit Emissions
518
Following the methodology summarized in Figure 1, the refinery emissions attributed to process
519
units are calculated. The national unit GHG and CAP emissions (including process emissions,
520
allocated combustion emissions, and allocated FWE-1 emissions) are listed in Table S18 in the SI,
521
and the unit emission shares are shown in Figure 4.
522 523 524 525
Figure 4. Shares of 2014 U.S. National Refinery Average GHG and CAP Emissions by Process Unit, After Allocations of Combustion Emissions andFWE-1, Based on Process Unit Heat and Steam Demand.
526
Refinery GHG and CAP emissions are mainly sourced from the atmospheric distillation tower,
527
catalytic reformer, FCC unit, hydrogen plant, and hydrotreating units (for diesel, gasoline, naphtha, 30
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528
and gasoil). These units have different capacities because they process different cuts (portions) of
529
crude slates and have different prevalence in U.S. refineries. For example, the atmospheric
530
distillation tower is present in every refinery and has the largest capacity, representing the overall
531
refinery crude process capability. In contrast, some other units, such as the coker and hydrocracker,
532
have smaller capacities because they process heavy cuts of refinery crudes and are often present
533
in more complex refineries. Considering these factors, it is useful to compare the unit emissions
534
intensity (dividing the total unit emissions by refinery unit throughput); the results are shown in
535
Table S19 in the SI.
536
Accounting for the capacity difference of various refinery units shows that the most emission-
537
intensive units are the lubricant production, thermal cracking, alkylation, catalytic reformer, and
538
FCC units. This is expected because these units are energy-intensive and thus bear greater emission
539
burdens from fuel combustion. This is consistent with previous research that indicated the
540
alkylation, catalytic reformer, and FCC units (the lubricant production and thermal cracking units
541
were not included in previous studies) are the leading refinery units in terms of GHG emissions[8,23]
542
and water consumption[30] (which is correlated to energy consumption). It is not surprising that the
543
lubricant production unit is very emission intensive because these processes are not only energy
544
intensive, and thus produce more combustion emissions, they also have high process VOC
545
emissions, likely due to solvent use and recovery.[29]
546
Refinery Final Products Derived from PRELIM V1.1
547
PRELIM V1.1 was used to model U.S. individual refinery operations (in 2014), using EIA-
548
reported crude input. The modeling of each refinery results in refinery final products based on
549
PRELIM refinery configurations. These model-derived refinery products amounts can diverge 31
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550
from the actual refinery products. Therefore, the model-resultant refinery final products are
551
compared to those of the EIA report, as described in Section 2; the results and discussions are
552
shown in Section 6 in the SI.
553
Refinery Emissions for Individual Refinery Final Products
554
The unit allocation factors to unit products (based on their energy contents), including still gas, are
555
shown in Figure S4 in the SI. As stated earlier, many units produce refinery still gas that is
556
subsequently combusted onsite to generate heat and steam. Emissions assigned to still gas from
557
each unit are pooled and reallocated to process units and subsequently to final products, based on
558
process unit heat and steam demand. The final allocation to units after the exhaustion of refinery
559
gas burdens is obtained after four iterations. The unit emissions after the reallocation of still gas
560
burdens are shown in Table S20 in the SI, and the unit allocation factors are shown in Figure S5
561
in the SI.
562
Combining the national or PADD refinery unit emission data with the refinery unit allocation
563
factors results in the emissions information for refinery products, including process emissions,
564
combustion emissions, and FWE-1, with still gas production burdens allocated to final products.
565
FWE-2 are allocated to final products based on their energy contents, independent of
566
PRELIM V1.1 use. Adding up the unit emissions attributed to refinery products and the FWE-2
567
attributed to refinery products produces the total emissions attributable to each refinery product.
568
The emissions allocated to each refinery product pool varies, and the shares of total facility
569
emissions are shown in Figure S7 in the SI. The emission contributions individual refinery
570
products make to total refinery emissions vary for each GHG or criterion pollutant. Gasoline BOB
32
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571
has the largest share for all pollutants, in the range of 47.7–57.9 wt%. Distillate/diesel has the
572
second largest share, in the range of 25.7–28.4 wt%.
573
Overall, dividing the refinery emissions allocated to refinery products (in kg/year) by refinery
574
products (in MJ) results in emissions per MJ of refinery product. The GHG and CAP emissions
575
for the production of refinery products are aggregated to the PADD and national levels. The
576
emissions associated with refinery products vary among PADDs, and the results are shown in
577
Table S24 in the SI. The comparison with literature data is shown in Figure S8 in the SI.
578
The emissions of the major refinery products—gasoline BOB, LPG, distillate, kerosene, and
579
residual fuel oil—are relatively consistent across all PADDs. In contrast, the less prevalent
580
products—lubricant, waxes, and miscellaneous products—show greater variation. The
581
miscellaneous products could include all finished products not classified elsewhere, such as
582
petrolatum, lube refining byproducts (aromatic extracts and tars), absorption oils, ramjet fuel,
583
petroleum rocket fuels, synthetic natural gas feedstocks, and specialty oils.[22] In the present study,
584
with the absence of sub‒category product information, the miscellaneous products are regarded as
585
aromatic extracts and tars from lubricant process. This is discussed further in Section 6 in the SI.
586
In particular, some GHG variations for lubricant, waxes, and miscellaneous petroleum products
587
can be attributed to the complex process of lubricant production, different sub-process units (e.g.,
588
hydrocracking versus solvent dewaxing), fewer datasets (e.g., PADD 2 has only one lubricant
589
production process), and the broad category of miscellaneous products, which impacts burden
590
allocation.
591
Combining the refinery emissions from each PADD produces the aggregate U.S. refinery GHG
592
emissions and CAP emissions, as shown in Figure 5. 33
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593 594 595 596 597
Figure 5. 2014 U.S. Refinery Onsite GHG Emissions and CAP Emissions Attributed to U.S. Refinery Products, National Aggregated Results (The left y‒axis refers to mg /MJ refinery product for CAPs and the right y‒axis refers to g CO2,eq/MJ refinery product for GHG).
598
In the present study, the GHG emissions and CAP emissions of gasoline BOB and LPG have
599
higher emissions than diesel/distillate, jet/kerosene, and aviation gasoline because the former two
600
are sourced from more energy-intensive conversion units (alkylation, catalytic reformer, FCC, etc.).
601
Unlike gasoline BOB, diesel is mainly produced from an atmospheric distillation tower, coker unit,
602
hydrocracker, and FCC. It is worth noting that diesel/distillate product has a sizeable CO2 emission
603
sourced from the hydrogen plant, owing to the extensive use of hydrogen for hydrotreating and
604
hydrocracking processes to produce clean (ultra-low sulfur) diesel (see Figure S9 in SI). Light
605
olefins have emissions similar to LPG, because they are mostly produced in parallel through a
606
series of conversion/separation units and treatment plants. The secondary refinery products,
607
lubricants, miscellaneous products, and wax have much higher emissions than the other refinery
608
products because they are produced from an energy-intensive lubricant production process. The 34
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609
detailed material and energy input attributed to each refinery product (upstream information) is
610
not investigated in the present study, as the present study solely focuses on refinery onsite
611
emissions.
612
The GHG emissions of the present study are also compared with those from previous research by
613
Elgowainy et al.,[8] Skone et al. (NETL report),[6] Cooney et al. (update of the NETL report),[11]
614
and PRELIM V1.1 results (those that were generated in our study during modeling of different
615
configurations), which are independent of NEI and GHGRP. These results are consistent, as
616
illustrated in Figure 6.
617 618 619
Figure 6. Comparison of U.S. Average Refinery Onsite GHG Emissions from this Study to Previously Published Research Results
620
The results from the present study match well with those of Elgowainy et al. [8] and are within the
621
low and high range of PRELIM V1.1. The Elgowainy et al.[8] study used LP modeling, a bottom-
622
up approach, to estimate refinery product GHG emissions for 70% of the U.S. refinery capacity.
623
The present study does not “create” refinery emissions by modeling, but instead allocates refinery-
35
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624
reported facility emission data to process units, then to refinery products, based on the refinery
625
unit energy use information from PRELIM V1.1.
626
Figure 6 shows that most refinery products have GHG emission values within the low and high
627
range of PRELIM V1.1 results, except for asphalt. This is probably because PRELIM V1.1 does
628
not include the lubricant production process and assumes that all asphalt comes from the asphalt
629
unit. In contrast, the present study assigns part of the lubricant production burden to a portion of
630
asphalt, which leads to higher asphalt GHG emissions because lubricant production is more
631
energy-intensive, and thus more GHG intensive, than asphalt units. The GHG emissions of
632
gasoline, diesel/distillate, and jet fuel/kerosene from the present study are lower than those of
633
NETL[6] and the research update by Cooney et al.[11] The following are some possible causes:
634
First, the Cooney et al. study[11] used PRELIM V1.1 to model U.S. individual refinery
635
operations and fuel consumption and to generate emission data. Although the model adopts
636
typical conditions for U.S. operations, the process unit might have a different efficiency, as real
637
world refineries do,[24] which generally is optimized and associated with efficient recycling of
638
internal heat and steam. The deviation in process unit efficiency might lead to an overestimation
639
of fuel consumption and thus higher facility emissions and subsequently systematic higher
640
emissions allocated to all refinery products. In addition, the model does not “customize”
641
operations or processing based on crude slates, so all crudes are set to have the same
642
intermediate products. This could cause overestimated energy requirements for high-quality
643
crudes in more complex conversions,[24] resulting in overestimation of GHG emissions. In
644
contrast, the present study only attributes the known, refinery-reported facility or unit
645
emissions[2,13] to individual products. These emissions are actual emissions based on 2014 U.S. 36
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646
refinery operations. PRELIM V1.1 is not used to create GHG emission values based on fuels
647
use; it is used only to guide allocation.
648
Second, the Cooney et al.[11] research does not include some secondary products (lubricant,
649
aromatics, wax, etc.). Thus, the burdens that should have been allocated to secondary products
650
shift to the main products (gasoline BOB, diesel/distillate, etc.), increasing the burdens on the
651
main products. In contrast, our study includes a more complete list of refinery products to share
652
the refinery operation burdens, leading to lower burdens for the main refinery products.
653
Note that the Cooney et al. research[11] used hydrogen allocation, while this study uses energy
654
allocation. The different allocation methods would change how the refinery GHG emissions are
655
attributed to the different refinery products, but would not alter the refinery overall GHG emissions.
656
Therefore, the different allocation methods are not the reason that the GHG emissions in the
657
Cooney et al.[11] study are systematically higher than those in the present study.
658
Unlike the research on the refinery products’ GHG emissions, research about the refinery products’
659
CAP emissions have rarely been reported. One conference paper (by the authors of the present
660
study)[34] summarized the allocation of individual refinery CAP emissions (from the 2014 NEI
661
database) to refinery products via LP modeling. That conference paper also reported the U.S.
662
national aggregate results derived from modeling 21 U.S. refineries (representing about 32% of
663
total U.S. refinery capacity in 2014). The comparison of current results with those of our previous
664
work using LP modeling are shown in Figure 7.
37
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665 666 667
Figure 7. Comparison of U.S. Average Refinery Product CAP Emissions from this Study to Sun et al. 2017[34] Derived from LP Modeling
668
In the Sun et al. 2017 work,[34] the CAP emissions of asphalt used the data for “heavy products.”
669
The heavy products category refers to miscellaneous final heavy products, which are specific to
670
individual refineries. It can include asphalt, light or heavy cycle oil, or heavy gas oil for sale.
671
Both sets of results are derived from the NEI dataset. This study uses PRELIM V1.1 as a platform
672
to execute the allocations. The previous study[34] used LP as a platform for allocation. Both results
673
show CAP emissions in the same order of magnitude, and there is good consistency for gasoline
674
BOB, diesel/distillate, jet/kerosene, residual fuel oil, petroleum coke, and asphalt. There is more
675
variation for the LPG and lubricant refinery products. In particular, the present study shows much
676
higher burdens for lubricant production than those derived from LP. The results of the present
677
study are expected to be more representative. This is because, relative to the results from LP
678
modeling,[34] the present study has more facility coverage with a higher production capacity (at the
679
national level), and conducts more accurate allocation due to the availability of energy uses of
680
lubricant production. 38
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681
The breakdown of the emissions associated with refinery products (U.S. average) is shown in
682
Table S25 in the SI. Consistent with the emissions per crude processed, for CO2, N2O, CO, NOX,
683
SO2, PM10, and PM2.5, most emissions are sourced from combustion. For VOCs and CH4, most
684
emissions are from FWEs.
685
The breakdown of the emissions associated with refinery products (U.S. average), by process unit,
686
are shown in Figure S9 to Figure S17 in the SI. The emission shares by process units vary
687
significantly with refinery product and pollutant type.
688
Future Work and Applications
689
The present study serves as an original exploratory work to develop a methodology and to
690
systematically benchmark U.S. refinery CAP emissions. Next efforts can focus on fine-tuning the
691
emissions allocated to refinery products by (1) modifying PRELIM V1.1 default configurations to
692
better match U.S. individual refineries, and (2) developing and using refinery specific crude slates
693
for individual refinery modeling.
694
The CAP and GHG emissions attributed to transportation fuels (e.g., gasoline BOB,
695
diesel/distillate and jet/kerosene fuel) can serve as air emissions baselines, against which the
696
environmental impact (CAP emission and GHG emission) of alternative transportation fuels
697
production (e.g., hydrogen production, biofuel production) can be evaluated. The CAP and GHG
698
emissions attributed to the production of some secondary products—such as asphalt, lubricant,
699
light olefins, wax, and others—fill a data gap for the quantitative analyses of air emissions
700
associated with basic materials manufacture, enabling the environmental evaluation of a number
701
of industries or industrial activities in modern society.
39
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702
In addition, the refinery process unit emission intensities are developed for GHG emissions and
703
CAP emissions. This information can be used to project future refinery emissions with varying
704
configurations and unit capacities, in response to ever-evolving energy landscape and fuel
705
regulations, volatile market demand, and many other factors. For example, EIA reports that since
706
2008, U.S. Gulf Coast refiners have shifted to lighter crudes due to the switch from heavier
707
imported crude to lighter domestic crude produced in Texas.[35] Meanwhile, EIA also reports that
708
PADD 2 refiners transitioned to heavier crudes[36] after 2010; this might be attributed to the
709
increased usage of discounted Canadian heavy oil. Regulatory driving forces also affect refinery
710
operations. For example, the upcoming International Convention for the Prevention of Pollution
711
from Ships (MARPOL) regulation,[37] which will come into effect in 2020, urges refineries to
712
provide low-sulfur marine fuels, which will likely result in increased usage of sweeter crude,[38] or
713
potentially drive refinery investment in unit additions or expansions (e.g., coker units).[39]
714
Meanwhile, the potential Reid Vapor Pressure waiver for E15 fuel
715
market shares for E15 fuel and subsequently refinery operations changes to reduce BOB volume
716
and produce different BOB recipes. These potential changes, along with other uncertain factors
717
not mentioned here, could profoundly influence refinery crude selection, operations adaptation, or
718
even configuration changes. In response to these dynamic changes, refineries will need to re-
719
optimize operations to maximize profits, which could increase or decrease energy use and
720
subsequent air emissions.
721
On the other side, refineries have succeeded in reducing air emissions significantly (especially for
722
NOx, SOx) in the past several decades, owing to the adoption of emission control technologies
723
(e.g., selective catalytic reduction (SCR) and ultra-low NOx burner) technology.[32] It is likely that
724
refineries will continue to curb air emissions (along with other environmental releases), driven by
[40]
could result in increased
40
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725
tightening regulations[38, 41] and economic gains from more efficient fuels use. The air emissions
726
reduction could be exercised by development in combustion control technology. For example,
727
recently one refinery in California adopted a new front-end fuel combustion technology that
728
reduced NOx emissions and CO emissions well below regional limits.[42] (Note that California is
729
among the regions with the most stringent regulatory requirements.) In addition, continuous
730
monitoring via more sensitive analytical instrumentation and responsive system controls of various
731
units (e.g., combustion, FCC unit, flare control, cooling tower, sulfur recovery unit, and so on),
732
could promote more efficient fuel combustion and mitigate process leak, thus reducing air
733
emissions.[43, 44]
734
Overall, the present study is the first, exploratory work to benchmark refinery CAP emissions
735
together with GHG emissions. The derived results of GHG and CAP emissions allocated to
736
refinery products establish baseline data to compare against future studies of refinery emissions
737
and against the environmental impacts of producing alternative or renewable fuels and chemicals.
738
In the future, a full life cycle analysis of various refinery products can be developed based on CAP
739
emission information for the recovery of various crude oils in conjunction with CAP emissions
740
measured for various refinery products applications, such as vehicle operations, asphalt for road
741
construction, olefins for petrochemical production and so on.
742
Supporting Information
743
Section 1: Additional information regarding facility coverage, energy uses used for investigating
744
the refinery fuels combustion emission factor, and emission factors for distillate, other fuel,
745
residual oil, and LPG. 41
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746
Section 2: Refinery emissions attributed to refinery crude throughput in each PADD.
747
Section 3: Calculations of U.S. refinery process unit capacity and energy use (heat, steam and
748
electricity), based on PRELIM modeling.
749
Section 4: Calculations of U.S. refinery emissions attributed to process units based on energy use
750
information
751
Sections 5 and 6: List of U.S. refinery products derived from PRELIM model and a comparison
752
with EIA report
753
Section 7: How unit emissions are attributed to unit products, especially for refinery still gas and
754
lubricant production processes.
755
Section 8: Air emissions attributed to individual refinery products produced in each PADD and
756
itemized by sources, emission type, and process units.
757
Acknowledgements
758
This research was supported by the Fuel Cell Technologies Office of the U.S. Department of
759
Energy’s Office of Energy Efficiency and Renewable Energy under Contract Number DE-AC02-
760
06CH11357. The authors are grateful to Fred Joseck from the U.S. Department of Energy’s Fuel
761
Cell Technologies Office for his guidance and support. The views and opinions of the authors
762
expressed herein do not necessarily state or reflect those of the United States Government or any
763
agency thereof. Neither the United States Government nor any agency thereof, nor any of their
764
employees, makes any warranty, expressed or implied, or assumes any legal liability or
42
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765
responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product,
766
or process disclosed, or represents that its use would not infringe privately owned rights.
43
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